EssKayz commented on issue #26619:
URL: https://github.com/apache/airflow/issues/26619#issuecomment-1256048784
This should be a working example, so essentially
```
dag = DAG('mockup_example',
# With this option, even when the start date is "one day ago" we
instruct airflow scheduler to only create
# a DAG Run for the most current instance of the DAG interval
series.
catchup=False,
default_args=dag_args,
default_view='graph',
schedule_interval=None, dagrun_timeout=timedelta(minutes=30))
def gen_multiprocess_example(
dag: DAG,
gen_task_id,
**kwargs
) -> TaskGroup:
with TaskGroup(dag=dag, group_id=f'mockup_{gen_task_id}',
prefix_group_id=False) as grp:
task = PythonOperator(
task_id=f'split_{gen_task_id}_data',
python_callable=split_example,
op_kwargs={
}
)
# This works, by utilizing a dirty hack
PythonOperator.partial(
task_id=f'process_{gen_task_id}_data',
python_callable=process_split_data,
op_kwargs={
}
).expand(
templates_dict=XComArg(task)
)
# This doesn't work, since the kwargs get expanded to
PythonOperator, not to the callable.
# PythonOperator.partial(
# task_id=f'process_{gen_task_id}_data',
# python_callable=process_split_data,
# op_kwargs={
# }
# ).expand_kwargs(
# XComArg(task)
# )
return grp
def split_example(**kwargs):
return [{'data': '1234', 'bucket_name': 'prod'}, {'data': '4321',
'bucket_name': 'test'}]
def process_split_data(data=None, bucket_name=None, templates_dict={},
**kwargs):
print('-' * 20)
print('data in process_func:', data)
print('bucket_name in process_func:', bucket_name)
print('templates_dict in process_func:', templates_dict)
print('-' * 20)
print(get_data(**templates_dict, **kwargs))
def get_data(data=None, bucket_name=None, **kwargs):
print('-' * 20)
print('data in get_data:', data)
print('bucket_name in get_data:', bucket_name)
print('-' * 20)
return data
with dag:
tg1 = gen_multiprocess_example(
dag,
gen_task_id='hope_this_helps'
)
```
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